European Renewable Energy Scenario

European Renewable Energy Scenario

The future of renewable energy (primarily solar and wind based) is widely considered to be simultaneously inevitable, yet, unpredictable, with both being heavily susceptible to fluctuating weather patterns. Various attempts have been made to better understand the relationship between emissions, weather and the environment, however such attempts are frequently restricted to specific emissions models, in a specific location and specific period of time, with no interplay between these variables.

However, recently a cross-country team with scientists from the United Kingdom, Ireland and Switzerland has used meteorological data from the past three decades and added accordingly predicted numbers up until 2030 to study the future of renewable energy. Their research found that while power generated through wind and solar will continue to be unpredictable, together they will be able to contribute 35% of the total European power production without a significant effect on energy prices or stability.

Furthermore, the team built five different scenarios to see how Europe’s atmosphere, including varying CO2 levels, weather-reliant factors and energy generation costs, will impact the energy landscape. The results show that European countries’ close integration means they can handle the variability well, and in the most positive of scenarios Europe could use renewable energy for over two thirds of their total energy production.

This comes at a time when prediction technology and data analytics continue to explode in popularity, for example, the strong favouring of digital twins in the wider IoT community, and across a number of sectors. Such an approach significantly decreases risk and maintenance costs/downtime in deploying new technologies, renewable energy methods included.

While this is hugely positive news, the model currently focuses on the two most known and in-use renewable energy methods, to the exclusion of numerous other renewable energy production methods that have shown great promise. Creating a similar updated model or adding in other renewable methods such as hydro energy would bring more value to the model, as well as extending the timeline from 2030 onwards. However, using historical data is, the best indicator for future atmospheric behavior we can leverage, and this information will be useful to many organisations in the energy sector.